docker_practice open source analysis

Learn and understand Docker&Container technologies, with real DevOps practice!

Project overview

⭐ 25771 · Go · Last activity on GitHub: 2026-01-03

GitHub: https://github.com/yeasy/docker_practice

Why it matters for engineering teams

docker_practice addresses the practical challenges software engineers face when learning and applying container technologies in real-world environments. It provides hands-on experience with Docker and related tools, helping teams understand containerisation, orchestration, and deployment workflows critical for modern cloud infrastructure. This open source tool for engineering teams is particularly suited to DevOps engineers, site reliability engineers, and backend developers who need to manage containerised applications at scale. With over 25,000 stars and active maintenance, it is a mature and reliable resource for production ready solutions. However, it is not the best choice for teams seeking a fully integrated enterprise platform or those new to container concepts, as it focuses more on practical learning than turnkey deployment systems.

When to use this project

docker_practice is an excellent choice for teams aiming to deepen their understanding of container and orchestration technologies through practical exercises. It is less suitable when a fully supported commercial container management platform is required or when rapid deployment without learning overhead is a priority.

Team fit and typical use cases

DevOps engineers and cloud infrastructure teams benefit most from docker_practice, using it to build and refine container workflows and orchestration strategies. It typically appears in products that rely on microservices architectures, continuous integration pipelines, and self hosted options for container management. Engineering teams use it as a hands-on resource to bridge the gap between theory and production deployment.

Topics and ecosystem

book cloud-computing container devops docker kubernetes linux mesos spark swarm

Activity and freshness

Latest commit on GitHub: 2026-01-03. Activity data is based on repeated RepoPi snapshots of the GitHub repository. It gives a quick, factual view of how alive the project is.